Anytime Capacity: Another notable contribution in [1]} focuses on the intersection of information and control theory, by studying the concept of anytime capacity. In this case, the aim of communication is specifically targeted on stabilizing an unstable linear process (e.g. a plant control loop). While previous works have focused on erasure channels [2]}, the work in hand addresses noisy channels. The focus is on a small-scale scalar system model with a single observer who communicated over a noisy channel with a single controller. The controller can send both control signals to the system and feedback to the observer with a one step delay. The main result is the “equivalence” between stabilization over noisy feedback channels and reliable communication over noisy channels with feedback. A key point in the model is that the decoder of the controller has to provide increasingly reliable estimates for all received past messages, as there is no side information about the message timing as required by the system. The reliability of the messages should increase sufficiently rapidly as time evolves to that the system remains stable.
